Modernize AI + Data Platform
Empowering business growth with our data engineering platform
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Our platform facilitates data streaming, broadcasting live transactions for downstream systems and third-party integration. We gather data from various sources, platforms, and environments to form data lakes, providing real-time data warehousing and analytics. We can also accommodate intricate disaster recovery and backup needs, including separating transactional systems from analytical loads for load management and automated schema/DDL evolution.
We leverage the power of automation to streamline dataflows and use machine learning to learn from remediation to scale faster. We help simplify complex processes by democratising data governance and data management.
We offer the capability to leverage smart technologies like pattern recognition, data cataloguing, data lineage, and machine learning. We help you organise your data at scale and with the right data governance practices, you can achieve organisation-wide collaboration on data ownership, curation, remediation, and reuse.
At Exponentia.ai, we are committed to assisting you with data governance by capturing and understanding data through discovery, profiling, and benchmarking tools and capabilities. For instance, we can automatically detect a piece of personal data, such as a Social Security number, within a new data set and trigger an alert.
To ensure that our Algorithms predict accurately, we strive to improve the quality of data with validation, data cleansing, and data enrichment. We manage data with metadata-driven ETL, ELT and data integration applications, to track and trace data pipelines with end-to-end data lineage.
We control your organisation’s diverse sources and massive volumes of data with tools that actively review, monitor, and document data. This allows it to be augmented by metadata to increase its relevance, searchability, accessibility, linkability, and compliance.
We work with you and your team to provide easy self-service tools that help you automate your data stewardship tasks so that you can focus on your business
Our modern data platform is designed to automate the daily mundane activities and streamline dataflows. We use machine learning to learn from remediation and scale faster, as well as to simplify data governance and data management. We also leverage smart technologies like pattern recognition, data cataloguing, data lineage, and machine learning to organise data at scale.
At Exponentia.ai, we are committed to assisting you with data governance by capturing and understanding data through discovery, profiling, and benchmarking tools and capabilities. For instance, we can automatically detect a piece of personal data, such as a Social Security number, within a new data set and trigger an alert.
To ensure that our Algorithms predict accurately, we strive to improve the quality of data with validation, data cleansing, and data enrichment. We manage data with metadata-driven ETL, ELT and data integration applications, to track and trace data pipelines with end-to-end data lineage.
We control your organisation’s diverse sources and massive volumes of data with tools that actively review, monitor, and document data. This allows it to be augmented by metadata to increase its relevance, searchability, accessibility, linkability, and compliance.
We work with you and your team to provide easy self-service tools that help you automate your data stewardship tasks so that you can focus on your business
Our modern data platform is designed to automate the daily mundane activities and streamline dataflows. We use machine learning to learn from remediation and scale faster, as well as to simplify data governance and data management. We also leverage smart technologies like pattern recognition, data cataloguing, data lineage, and machine learning to organise data at scale.
We leverage the power of automation to streamline dataflows and use machine learning to learn from remediation to scale faster. We help simplify complex processes by democratising data governance and data management.
We offer a wide range of services to cater to your diverse needs. This includes consulting, system integration, data strategy and management, data engineering, data science, business intelligence, artificial intelligence, and cognitive computing. Our team of experts can handle the entire analytics lifecycle, from data collection and preparation to data analysis and visualisation. Whether you’re using AWS, Microsoft technologies, or your custom environments, we’ve got you covered.
We offer continuous monitoring for scheduled jobs, reports, tasks, and more on top of generating audit reports, providing you with a comprehensive overview of your operations.
Our email alerts provide your teams with failure logs enabling them to quickly identify and address any issues, minimising downtime, and disruption.
We actively tackle challenges by rerunning jobs, editing reports, and escalating as necessary. Our end-to-end ownership of Business As Usual (BAU) operations lets your team focus on other high-value tasks.
At Exponentia.ai, we’re working with customers to pioneer analytics as a service with AI. Our core domain expertise lies across BFSI particularly Insurance and NBFC’s on top of CPG and manufacturing.
Business-as-Usual (BAU) Processes require continuous monitoring, issue resolution & root cause analyses along with periodic upgrades and change request implementations. We help you avoid recurring failures using standard preventive measures while we automate manual processes to avoid human errors, delays and inaccuracies.
Data profiling, lineage mapping, and dependency analysis
Scalable target architecture and migration strategy design
Automated ETL/ELT pipelines with data cleansing and standardization
Quality checks, compliance controls, and full traceability
Performance tuning and enablement of analytics, AI, and reporting
Stop funding closed SAS environments (typically 700K–1M annually) and redirect that capital toward GenAI and machine learning.
Transition from fragmented legacy operations to a modern Python, Apache Spark, and MLflow ecosystem.
Safely migrate mission-critical actuarial and risk models using deterministic validation and functional parity.
Seamless migration from legacy systems to scalable cloud and modern data platforms
Re-platform and optimize ETL pipelines and analytics ecosystems
Unify fragmented data across systems, geographies, and business units
Enable secure, governed data movement across hybrid and multi-cloud environments
Leverage automation and ML to accelerate migration with accuracy and resilience
We systematically resolve the technical traps that break 60–70% of unsupported migrations, including complex procedural data steps, SAS merge semantics, and ANSI NULL handling.
We enforce 100% row-perfect functional parity gates prior to any production cutover.
Before any commitment, our 6–8 week diagnostic delivers a SAS Estate Scorecard, an AI Roadmap, and a fully costed Migration Business Case.
Reduce infrastructure and operational costs through efficient architectures
Accelerate access to analytics and decision-ready data
Improve data engineering efficiency through automation
Enhance compliance, data quality, and traceability
Enable advanced analytics, ML, and AI use cases
Achieve 70–90% automated SAS-to-PySpark conversion with per-program confidence scoring.
Stand up real-time pricing and predictive intelligence alongside the migration process, not years after it.
Instant unification of data engineering and AI governance under Databricks Unity Catalog.
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Automated, scalable migration powered by modern data engineering frameworks
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Structured approach to de-risk complex enterprise programs
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From strategy and execution to post-migration optimization
Strong capabilities across cloud, data, and analytics platforms
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Focused on measurable business impact, not just technical migration
Unlock $380K to $1.2M in three-year savings by avoiding massive legacy renewals.
Transform multi-day legacy batch workflows into serverless operations that run in under 3 hours.
Turn your next SAS renewal into both your AI platform and your AI budget
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